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Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.

Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.

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  1. Brunel University Research Archive

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Concurrent validity, test–retest reliability, and normative properties of the ignite app: A cognitive assessment for frontotemporal dementia. See

Objective: Digital biomarkers can provide frequent, real-time monitoring of health-related behavior and could play an important role in the assessment of cognition in frontotemporal dementia (FTD). However, the validity and reliability of digital biomarkers as measures of cognitive function must ...

Neuroanatomical normative modelling in frontotemporal lobar degeneration: higher heterogeneity in the behavioural variant See

Introduction: Frontotemporal lobar degeneration (FTLD) includes heterogenous diseases: behavioural variant frontotemporal dementia (bvFTD), primary progressive aphasias (PPA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). We applied neuroanatomical normative modelling to quantify individual atro...

New calculus rules of relative subdifferentials and applications to constrained optimization problems See

This paper investigates properties and calculus rules, including new calculation formulas of chain rules and maximum-pointwise rules for the relative subdifferentials of nondifferentiable functions. Based on these properties and calculation rules, we establish novel optimality conditions without normal con...

Information Theoretic Learning for Diffusion Models with Warm Start See

Generative models that maximize model likelihood have gained traction in many practical settings. Among them, perturbation-based approaches underpin many state-of-the-art likelihood estimation models, yet they often face slow convergence and limited theoretical understanding. In this paper, we derive a...

Three-Dimensional Finite Element Modeling of Drilling-Induced Damage in S2/FM94 Glass-Fiber-Reinforced Polymers (GFRPs) See

Considering that the machining of composites particularly fiber-reinforced polymer composites (FRPCs) has remained a challenge associated with their heterogeneity and anisotropic nature, damage caused by drilling operations can be considerably mitigated by following optimum cutting parameters. In this work...

Effects of interventions on sedentary behaviour and cardiovascular disease biomarkers in individuals with spinal cord injury: a systematic review See

...

COMPARATIVE STUDY OF DEEP CO-AXIAL CLOSED LOOP AND U-SHAPED WELLBORE GEOTHERMAL SYSTEMS See

Until recently, geothermal energy has been limited to regions with favorable subsurface conditions. Most installed geothermal systems are open, using two wells for fluid injection and extraction. Closed-loop systems have historically been used in low-depth installations as ground source heat pump...

PARAMETRIC STUDY OF THE THERMAL-HYDRAULIC CHARACTERISTICS OF DEEP BOREHOLE CO-AXIAL HEAT EXCHANGER IN A GEOTHERMAL WELL See

Geothermal energy constitutes an additional option for energy planners and can have significant advantages when compared to other renewable sources. The work presented here relates to geothermal wells located in areas of average and high geothermal gradients, i.e. 30 and 80 K/km th...

Optimality and solutions for conic robust multiobjective programs See

This paper presents a robust framework for handling a conic multiobjective linear optimization problem, where the objective and constraint functions are involving affinely parameterized data uncertainties. More precisely, we examine optimality conditions and calculate efficient solutions of the conic ...

Decomposition for Large-Scale Optimization Problems: An Overview See

Formalizing complex processes and phenomena of a real-world problem may require a large number of variables and constraints, resulting in what is termed a large-scale optimization problem. Nowadays, such large-scale optimization problems are solved using computing machines, leading to an enormous...

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Author
  • 1314 Wang, Z
  • 1308 Adam, W
  • 1305 Bergauer, T
  • 1304 Dragicevic, M
  • 1303 Clerbaux, B
  • 1297 Lowette, S
  • 1291 Waltenberger, W
  • 1290 Vanlaer, P
  • 1285 Liko, D
  • 1283 Jeitler, M
  • . next >
Subject
  • 275 CMS
  • 265 Physics
  • 219 Science & Technology
  • 165 COVID-19
  • 164 Hadron-Hadron scattering (experim...
  • 139 machine learning
  • 129 deep learning
  • 115 artificial intelligence
  • 103 sustainability
  • 101 Physical Sciences
  • . next >
Date issued
  • 29009 2000 - 2026
  • 1232 1900 - 1999
  • 3 1830 - 1899
Library (c) Brunel University. Updated: December 19th,2023

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